[u' @inproceedings{almeida_towards_2008, address = {Tenerife, Spain}, title = {Towards a {Solution} to {Extract} {Knowledge} from the {Social} {Web}}, abstract = {Ontologies are a useful and attractive tool for representing knowledge. In fact, if all the documents in the web were represented with ontologies, the job of search engines, automatic document processors, etc. would be much easier. However, ontologies are too complex to be used by the general public and, so far, are used only by specialized users. Nonetheless, a more informal type of classifying resources is becoming increasingly popular amongst the general public: social tagging or folksonomies. Many popular websites (del.icio.us, Flickr, Technorati...) allow users to participate by annotating web content using tags. Although they provide an easy way to collaboratively create knowledge, these tags are difficult to machine-process. In this paper, we propose mapping folksonomies into more estructured metadata so that the information in social tagging systems will be made easier to process. To that effect, we present the design and implementation of a software application, folk2onto, that can be trained to map tags into an ontology.}, booktitle = {Proceedings of the {Workshop} on {Knowledge} {Reuse} and {Reengineering} over the {Web}}, author = {Almeida, Aitor and Sotomayor, Borja and Abaitua, Joseba and L\xf3pez-De-Ipi\xf1a, Diego}, month = jun, year = {2008}, keywords = {Artificial Intelligence, Data analysis, NLP, collonbus, del.icio.us, folksonomies, machine learning, natural language processing, ontologies, social networks, wordnet}, } ']